Doctors may soon be able to diagnose an elusive form of heart disease within seconds by using an AI model developed at ...

Hospitals do not always have the opportunity to collect data in tidy, uniform batches. A clinic may have a handful of carefully labeled images from one scanner while holding thousands of unlabeled ...

T.J. Thomson receives funding from the Australian Research Council. He is an affiliate with the ARC Centre of Excellence for Automated Decision Making & Society. Aaron J. Snoswell receives research ...

This repository contains the source code, scripts, and supplementary materials for the paper: "A New Hybrid Model for Improving Outlier Detection Using Combined Autoencoder and Variational Autoencoder ...

There was an error while loading. Please reload this page. Project: Real-Time Anomaly Detection using Object Detector and USB Camera Overview This project implements ...

ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...

The region, known as the South Atlantic Anomaly, has grown by an area nearly half the size of continental Europe, sprouting a lobe in the direction of Africa where the field is weakening the fastest.

ABSTRACT: This work contributes to the development of intelligent data-driven approaches to improve intrusion management in smart IoT environments. The proposed model combines a hybrid ...

James is a published author with multiple pop-history and science books to his name. He specializes in history, space, strange science, and anything out of the ordinary.View full profile James is a ...

We showcase a novel unsupervised learning method with a Convolutional Variational Autoencoder (CVAE) model that can automatically classify and cluster different types ...